code: def test_shuffling_batcher_grid(
      batch_size, local_shuffle_buffer_size
  ):
      ds = ray.data.range_tensor(10000, shape=(130,))
      start = time.time()
      count = 0
      for batch in ds.iter_batches(
          batch_size=batch_size,
          local_shuffle_buffer_size=local_shuffle_buffer_size,
      ):
          count += len(batch["data"])
      print((ds.size_bytes() / 1e9) / (time.time() - start), "GB/s")
      assert count == 10000
  
file_path: ray/python/ray/data/tests/test_batcher.py
imports: import time
  import pyarrow
  import pytest
  import ray
  from ray.data._internal.batcher import Batcher, ShufflingBatcher
label_desc: Use image node_id 4 for calling a global function with example usage: test_shuffling_batcher_grid(batch_size, local_shuffle_buffer_size) without return types